Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
test = pd.Series([pd.date_range("2020-01-01T00:00:00Z", "2020-01-01T02:00:00Z", freq="1h", unit="ms")])
test.explode().dtypeIssue Description
The docs for pd.date_range state that the unit keyword argument is the resolution of timestamps in the returned DatetimeIndex, which is true---and counter to the usage of unit elsewhere, e.g. in pd.to_datetime. Regardless of this discrepancy, explode does not respect the millisecond resolution of timestamps in a DatetimeIndex, converting them to nanosecond resolution in the returned Series or DataFrame.
Expected Behavior
dtypes should not be changed by explode.
Installed Versions
INSTALLED VERSIONS
commit : 2cc3762
python : 3.11.13
python-bits : 64
OS : Linux
OS-release : 5.15.0-139-generic
Version : #149~20.04.1-Ubuntu SMP Wed Apr 16 08:29:56 UTC 2025
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.3.0
numpy : 1.26.4
pytz : 2025.2
dateutil : 2.9.0.post0
pip : 25.1.1
Cython : None
sphinx : 8.2.3
IPython : 9.3.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.13.4
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2025.5.1
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : 3.1.6
lxml.etree : None
matplotlib : 3.10.3
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 20.0.0
pyreadstat : None
pytest : 8.4.0
python-calamine : None
pyxlsb : None
s3fs : 2025.5.1
scipy : 1.15.3
sqlalchemy : 2.0.41
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2025.2
qtpy : None
pyqt5 : None